Optimizing likelihood models for particle trajectory segmentation in multi-state systems

Dylan C Young, Jan Scrimgeour

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DOI: 10.1088/1478-3975/aacd5a
Published: 2018-07-06
Container: Physical Biology
Publisher: IOP Publishing
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1088/1478-3975/aacd5a,
  title = {Optimizing likelihood models for particle trajectory segmentation in multi-state systems},
  author = {Dylan C Young and Jan Scrimgeour},
  year = {2018},
  journal = {Physical Biology},
  doi = {10.1088/1478-3975/aacd5a},
  url = {https://doi.org/10.1088/1478-3975/aacd5a}
}

RIS

TY  - JOUR
TI  - Optimizing likelihood models for particle trajectory segmentation in multi-state systems
AU  - Dylan C Young
AU  - Jan Scrimgeour
PY  - 2018
JO  - Physical Biology
DO  - 10.1088/1478-3975/aacd5a
UR  - https://doi.org/10.1088/1478-3975/aacd5a
ER  -

APA

Young, D. C., & Scrimgeour, J. (2018). Optimizing likelihood models for particle trajectory segmentation in multi-state systems. Physical Biology. https://doi.org/10.1088/1478-3975/aacd5a

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crossref · retrieved 2026-11-10T11:29:01.573Z